Ghent University Academic Bibliography

Show Sort by

Your filters: cql: author="Lootens, Peter" or (type any "bookEditor journalEditor issueEditor" and editor="Lootens, ...

Add to list
- Journal Article
- open access
Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses

Tom De Swaef, Wouter Maes (UGent) , Jonas Aper, Joost Baert, Mathias Cougnon (UGent) , Dirk Reheul (UGent) , Kathy Steppe (UGent) , Isabel Roldàn-Ruiz (UGent) and Peter Lootens

(2021) Remote Sensing. 13(1).
Add to list
Turgor-driven plant growth applied in a soybean functional-structural plant model

Jonas Coussement (UGent) , Tom De Swaef, Peter Lootens and Kathy Steppe (UGent)

(2020) ANNALS OF BOTANY. 126(4). p.729-744
Add to list
- Journal Article
- A1
- open access
Gloxinia—an open-source sensing platform to monitor the dynamic responses of plants

Olivier Pieters (UGent) , Tom De Swaef, Peter Lootens, Michiel Stock (UGent) , Isabel Roldàn-Ruiz (UGent) and Francis wyffels (UGent)

(2020) SENSORS. 20(11).
Add to list
- Research Data
Close range hyperspectral camera dataset with high temporal resolution of strawberry with eco-physiological data of one leaf

Olivier Pieters (UGent) , Tom De Swaef, Peter Lootens, Michiel Stock (UGent) , Isabel Roldàn-Ruiz (UGent) and Francis wyffels (UGent)

(2020)
Add to list
- Research Data
High-resolution time series of leaf length and leaf thickness of strawberry and tomato measured in a growth chamber

Olivier Pieters (UGent) , Tom De Swaef, Peter Lootens, Michiel Stock (UGent) , Isabel Roldàn-Ruiz (UGent) and Francis wyffels (UGent)

(2020)
Add to list
Limitations of snapshot hyperspectral cameras to monitor plant response dynamics in stress-free conditions

Olivier Pieters (UGent) , Tom De Swaef, Peter Lootens, Michiel Stock (UGent) , Isabel Roldàn-Ruiz (UGent) and Francis wyffels (UGent)

(2020) COMPUTERS AND ELECTRONICS IN AGRICULTURE. 179.
Add to list
Automatic wheat ear counting using machine learning based on RGB UAV imagery

Jose A. Fernandez‐Gallego, Peter Lootens, Irene Borra‐Serrano, Veerle Derycke (UGent) , Geert Haesaert (UGent) , Isabel Roldàn-Ruiz (UGent) , Jose L. Araus and Shawn C. Kefauver

(2020) PLANT JOURNAL. 103(4). p.1603-1613
Add to list
Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery

Junfeng Gao (UGent) , David Nuyttens, Peter Lootens, Yong He and Jan Pieters (UGent)

(2018) BIOSYSTEMS ENGINEERING. 170. p.39-50
Add to list
Introducing turgor-driven growth dynamics into functional-structural plant models

Jonas Coussement (UGent) , Tom De Swaef, Peter Lootens, Isabel Roldàn-Ruiz (UGent) and Kathy Steppe (UGent)

(2018) ANNALS OF BOTANY. 121(5). p.849-861
Add to list
- Journal Article
- A1
- open access
A flexible geometric model for leaf shape descriptions with high accuracy

Jonas Coussement (UGent) , Kathy Steppe (UGent) , Peter Lootens, Isabel Roldàn-Ruiz (UGent) and Tom De Swaef

(2018) SILVA FENNICA. 52(2).

Academic Bibliography

Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses

Turgor-driven plant growth applied in a soybean functional-structural plant model

Gloxinia—an open-source sensing platform to monitor the dynamic responses of plants

Close range hyperspectral camera dataset with high temporal resolution of strawberry with eco-physiological data of one leaf

High-resolution time series of leaf length and leaf thickness of strawberry and tomato measured in a growth chamber

Limitations of snapshot hyperspectral cameras to monitor plant response dynamics in stress-free conditions

Automatic wheat ear counting using machine learning based on RGB UAV imagery

Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery

Introducing turgor-driven growth dynamics into functional-structural plant models

A flexible geometric model for leaf shape descriptions with high accuracy

Contents

Support

Contact